Automatic imaging device selection for video analytics

ABSTRACT

A suitable imaging device for capturing images of an object or an area of interest may be automatically selected based on information regarding the locations and/or other operational properties of a plurality of imaging devices, and a location of the object or the area of interest. One or more geometric models of the fields of view of the imaging devices may be generated, and whether the object or the area of interest falls within one or more of the fields of view may be determined using such models. Where multiple imaging devices may include the object or the area of interest, within a field of view, the imaging device having the most suitable image, e.g., the largest or highest resolution image of the object or the area of interest, may be selected.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/137,973, filed Dec. 20, 2013, the contents of which are incorporatedby reference herein in their entirety.

BACKGROUND

Video cameras are frequently used for the purpose of conductingsurveillance or monitoring operations. Such cameras may be aligned tocapture images of actions or events within their respective fields ofview, and information regarding the captured images or the actions orevents may be recorded and subjected to further analysis in order toidentify aspects, elements or features of the content expressed therein.For this purpose, video cameras may be provided alone or in groups, andmay be programmed to recognize when an action or event has occurred,such as when a frame-to-frame analysis of video imagery suggests that apredetermined threshold has been exceeded or that a predeterminedcondition has been satisfied, or when the analysis otherwise implies theoccurrence of the action or the event based on information captured bythe cameras.

Typically, when a group or array of cameras is provided for the purposeof conducting an analysis of the content expressed in one or more stillor moving images, one of the video cameras of the group or array ismanually selected. Next, an area of interest in a field of view of thecamera is identified. Such an area may constitute some or all of thepixels of the field of view. Finally, an activity that may occur withinthe field of view may be identified according to one or moffocalrecontent-based analyses.

The process of selecting one or more of a plurality of cameras forconducting video analytics for a specific purpose can be complicated bygeographic considerations and real-world constraints. For example,without conducting extensive trial-and-error analyses, or individuallyevaluating the suitability of each of the cameras for the specificpurpose, there is currently no way to discern which of the plurality ofcameras would provide the best or most advantageous views with regard tothe specific purpose. Particularly in time-critical situations or inever-changing environments, current systems and methods for identifyingappropriate cameras for conducting video analytics are inadequate inthis regard. Additionally, no such systems or methods may be appliedforensically, that is, to determine which of a plurality of cameras mayhave captured information regarding an event of interest that hasalready occurred. Rather, the information captured by each of theplurality of cameras must be individually evaluated in order todetermine whether one or more of the cameras recorded informationregarding the event of interest, or to evaluate the quality of suchinformation.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A, 1B, 1C, 1D and 1E are views of components of one system forautomatically selecting imaging devices for video analytics, inaccordance with embodiments of the present disclosure.

FIG. 2 is a block diagram of components of one system for automaticallyselecting imaging devices for video analytics, in accordance withembodiments of the present disclosure.

FIG. 3 is a flow chart of one process for automatically selectingimaging devices for video analytics, in accordance with embodiments ofthe present disclosure.

FIGS. 4A and 4B are views of one system for automatically selectingimaging devices for video analytics, in accordance with embodiments ofthe present disclosure.

FIG. 5 is a flow chart of one process for automatically selectingimaging devices for video analytics, in accordance with embodiments ofthe present disclosure.

FIG. 6 is a flow chart of one process for automatically selectingimaging devices for video analytics, in accordance with embodiments ofthe present disclosure.

FIG. 7 is a view of one system for automatically selecting imagingdevices for video analytics, in accordance with embodiments of thepresent disclosure.

DETAILED DESCRIPTION

As is set forth in greater detail below, the present disclosure isdirected to the automatic selection of imaging devices such as camerasfor use in content-based analytics. Specifically, the systems andmethods are directed to determining the geographic locations andoperational properties (e.g., orientations, attributes or capacities) ofa plurality of imaging devices, as well as a geographic location of oneor more areas or objects of interest. Upon calculating or otherwisedetermining a field of view or other coverage zone associated with theplurality of devices, the systems and methods disclosed herein maydetermine not only how many of the plurality of devices may provideviews of the areas or objects of interest but also which of theplurality of devices provides a superior or preferred view. Once animaging device or devices having the areas or objects of interest infields of view have been identified, the content of the images capturedby such devices may be analyzed to determine whether one or more suchimages indicate that an item is present, or that a condition, a statusor an event has occurred, according to any given triggering events ormetrics, or other relevant thresholds. Such triggering events, metrics,or thresholds may be associated with a recognition of a particular itemor object within a field of view of an imaging device, or a movement byone or more items or objects within the field of view, or any othervisually perceptible thing or action.

The analyses disclosed herein may be provided in real time, or innear-real time, with regard to the ongoing operation of a plurality ofimaging devices (e.g., cameras), i.e., to identify which imaging devicemay have a suitable or appropriate view of an area or an object ofinterest. Alternatively, such analyses may be provided forensically,i.e., in retrospect, or after the fact, with regard to the operation ofthe plurality of imaging devices, and may be used to determine one ormore of such imaging devices to capture still or moving images of thearea or the object of interest.

Referring to FIGS. 1A, 1B, 1C, 1D and 1E, views of components of onesystem 100 for automatically selecting imaging devices for videoanalytics in accordance with embodiments of the present disclosure areshown. The system 100 includes an object 102 within fields of view offour imaging devices 120A, 120B, 120C, 120D. As is shown in FIGS. 1A and1B, a location of the imaging device 120A is indicated by coordinatesx_(A), y_(A), z_(A), and a field of view of the imaging device 120A isshown by an angle γ_(A). The imaging device 120A is shown as having anaxis of orientation AXIS_(A). Similarly, locations of the imagingdevices 120B, 120C, 120D are indicated by coordinates x_(B), y_(B),z_(B); x_(C), y_(C), z_(C); and x_(D), y_(D), z_(D), and fields of viewof the imaging device 120B, 120C, 120D are shown by angles γ_(B), γ_(C)and γ_(D), and the axes of orientation AXIS_(B), AXIS_(C), AXIS_(D) ofthe imaging devices 120B, 120C, 120D are also shown. As is also shown inFIGS. 1A and 1B, a location of the object 102 is indicated bycoordinates x₁, y₁, z₁. Therefore, according to some embodiments, thesystems and methods disclosed herein are directed to identifying notonly one or more of a plurality of imaging devices which may have a viewof an object or area of interest, i.e., which of the imaging devices120A, 120B, 120C, 120D of FIGS. 1A and 1B may have the object 102 intheir respective fields of view along their respective axes oforientation, but also which pixels of which imaging devices may have theobject in their fields of view, and establishing one or more thresholdsor conditions for generating and issuing one or more alarm or alertsignals or messages.

Referring to FIGS. 1C and 1D, an orientation of the imaging device 120Cof FIGS. 1A and 1B about an axis AXIS_(C) is shown. The axis oforientation AXIS_(C) is expressed as having a roll angle of rotationω_(C) of the axis of orientation with respect to the x-axis, a pitchangle of rotation φ_(C) of the axis of orientation with respect to they-axis and a yaw angle of rotation κ_(C) of the axis of orientation withrespect to the z-axis.

The scope and extent of the information that may be captured by theimaging devices 120A, 120B, 120C, 120D of FIGS. 1A and 1B is a functionof not only the respective locations of the imaging devices but alsotheir respective orientations and configurations. Referring to FIG. 1E,a view of the object 102 captured by the imaging device 120C of FIGS.1A, 1B and 1C is shown. The view of the object 102 shown in FIG. 1E isexpressed in a back plane having dimensions defined by the position ofthe imaging device 120C, as indicated by the coordinates x_(C), y_(C),z_(C) shown in FIGS. 1A, 1B and 1C, as well as the axis of orientationAXIS_(C) of the imaging device 120C, as indicated by the roll angleω_(C), the pitch angle φ_(C) and the yaw angle κ_(C), as shown in FIG.1D, and the field of view of the imaging device 120C, as indicated bythe angle γ_(C), as shown in FIGS. 1A, 1B and 1C. Based on the position,the axis of orientation and the field of view of the imaging device120C, one or more still or moving images of the object 102 may beformed, such as is shown in FIG. 1E. Furthermore, the specific locationof the object 102 within the field of view (i.e., the pixels of thefield of view in which the object 102 appears) of the imaging device120C may be identified according to an optical transfer function of theimaging device (or a transfer function of a lens of the imaging device).

Some imaging devices, such as a digital camera, operates by capturinglight that is reflected from objects, by calculating or assigning one ormore quantitative values to aspects of the reflected light, e.g.,pixels, and by generating an output based on such values, or by storingsuch values in one or more data stores. Digital cameras may include oneor more sensors having one or more filters associated therewith, andsuch sensors may detect information regarding aspects of any number ofpixels of the reflected light corresponding to one or more base colors(e.g., red, green or blue) of the reflected light. Such sensors maygenerate data files including such information, and store such datafiles in one or more onboard or accessible data stores (e.g., a digitalvideo recorder, or “DVR”), as well as one or more removable data stores(e.g., flash memory devices), or displayed on one or more broadcast orclosed-circuit television networks, or over a computer network as theInternet. Data files that are stored in one or more data stores may beprinted onto paper, presented on one or more computer displays, orsubjected to one or more analyses, such as to identify items expressedtherein.

Reflected light may be captured or detected by a digital camera if thereflected light is within the camera's field of view. As is discussedabove, a field of view of a camera is defined as a function of adistance between a sensor and a lens, viz., a focal length, within thecamera, as well as a location of the camera and an angular orientationof the camera's lens. Where an object appears within a depth of field,or a distance within the field of view where the clarity and focus issufficiently sharp, a digital camera may capture light that is reflectedoff objects of any kind to a sufficiently high degree of resolutionusing one or more sensors thereof, and store information regarding thereflected light in one or more data files.

Many imaging devices also include manual or automatic features formodifying their respective fields of view or orientations. For example,a digital camera may be configured in a fixed position, or with a fixedfocal length (e.g., fixed-focus lenses) or angular orientation.Alternatively, an imaging device may include one or more motorizedfeatures for adjusting a position of the imaging device, or foradjusting either the focal length (e.g., zooming the imaging device) orthe angular orientation (e.g., the roll angle, the pitch angle or theyaw angle), by causing a change in the distance between the sensor andthe lens (e.g., optical zoom lenses or digital zoom lenses), a change inthe location of the imaging device, or a change in one or more of theangles defining the angular orientation.

For example, a digital camera may be hard-mounted to a support ormounting that maintains the cameras in a fixed configuration or anglewith respect to one, two or three axes. Alternatively, however, adigital camera may be provided with one or more motors and/orcontrollers for manually or automatically operating one or more of thecomponents, or for reorienting the axis or direction of the cameras,i.e., by panning or tilting such cameras. Panning a camera may cause arotation within a horizontal axis or about a vertical axis (e.g., ayaw), while tilting a camera may cause a rotation within a verticalplane or about a horizontal axis (e.g., a pitch). Additionally, a cameramay be rolled, or rotated about its axis of rotation, and within a planethat is perpendicular to the axis of rotation and substantially parallelto a field of view of the camera.

Furthermore, some modern imaging devices may digitally or electronicallyadjust an image identified in a field of view of an imaging device,subject to the physical and operational constraints of the imagingdevices. For example, a digital camera may virtually stretch or condensethe pixels of an image in order to focus or broaden the field of view ofthe digital camera, and also translate one or more portions of imageswithin the field of view. Imaging devices having optically adjustablefocal lengths or axes of orientation are commonly referred to aspan-tilt-zoom (or “PTZ”) imaging devices, while imaging devices havingdigitally or electronically adjustable zooming or translating featuresare commonly referred to as electronic PTZ (or “ePTZ”) imaging devices.

Information and/or data regarding features or objects expressed in adigital photograph, including colors, textures or outlines of theobjects, may be extracted from the photograph in any number of ways. Forexample, colors of pixels, or of groups of pixels, in a digitalphotograph may be determined and quantified according to one or morestandards, e.g., the RGB (“red-green-blue”) color model, in which theportions of red, green or blue in a pixel are expressed in threecorresponding numbers ranging from 0 to 255 in value, or a hexadecimalmodel, in which a color of a pixel is expressed in a six-character code,wherein each of the characters may have a range of sixteen. Moreover,textures or features of objects expressed in a digital photograph may beidentified using one or more computer-based methods, such as byidentifying changes in intensities within regions or sectors of thephotograph, or by defining areas of a photograph corresponding tospecific surfaces. Furthermore, outlines of objects expressed in adigital photograph may be identified using one or more algorithms ormachine-learning tools. Some such algorithms or tools may recognizeedges, contours or outlines of objects in a digital photograph, or ofportions of objects in the digital photograph, and may match the edges,contours or outlines of the objects against information regarding edges,contours or outlines of known objects, which may be stored in one ormore data stores.

When imaging devices are utilized in applications such as securitymonitoring or surveillance, a single imaging device may be provided, orone or more imaging devices may be provided in a matrix, array or otherstrategic configuration. For example, where the video monitoring of anobject or area of interest is desired, a single imaging device may beplaced in a location and an orientation in which the object or area ofinterest remains in the imaging device's field of view, or may bereasonably accessed by the imaging device and placed within the imagingdevice's field of view. Alternatively, a plurality of imaging devicesmay be placed in locations and orientations in which various aspects ofthe object or the area of interest may be captured. Such imaging devicesmay be functionally identical, or may include one or more differentunique sets of attributes or operational capacities.

The systems and methods of the present disclosure are directed toautomatically selecting one or more of a plurality of imaging devices,such as imaging devices, for a content-based analysis of an object or anarea of interest. The imaging devices may be selected by identifying thelocations of the imaging devices, and of the object or the area ofinterest, and determining, based on the operational properties (e.g.,orientations, attributes or capacities) of the imaging devices, thefields of view or coverage zones associated with each of the imagingdevices. According to some embodiments of the present disclosure, thefields of view or coverage zones for each of the imaging devices may bedetermined by generating one or more geometric or mathematical models ofthe fields of view or coverage zones, such as by defining a geometricsection in free space in the form of one or more virtual conical orfrustoconical sections, or pyramidal or frustopyramidal sections,according to a coordinate system.

A field of view of an imaging device may thus be defined by a positionof the imaging device, a dimension of an image sensor and a focal lengthbetween a lens and an image sensor of the imaging device, as well as aroll angle, a pitch angle and a yaw angle of the imaging device. Forexample, one conical or pyramidal section corresponding to a field ofview of an imaging device may be centered about an axis of orientationof the imaging device and may have an origin located at a lens of theimaging device. The position and orientation of the imaging devices, andthe positions of the objects or areas of interest, may be expressedaccording to any coordinate system, and may be defined with regard to asingle coordinate point, or with regard to coordinates of one or moretwo-dimensional line segments or geometric sections, orthree-dimensional volumes defined by such segments or sections.

In this regard, the systems and methods of the present disclosure maydetermine not only whether one of a plurality of imaging devicesincludes the object or the area of interest within a field of view, butalso which of the imaging devices, or which of the pixels within suchimaging devices, provides the best or most advantageous image of theobject or area of interest, i.e., the image of the object that has asufficiently large size or level of clarity or resolution. Moreover, thesystems and methods of the present disclosure may be used not only withimaging devices or other imaging devices but also in association withany form of sensor.

Once an imaging device including an object or area of interest within afield of view and in an appropriate size, or level of clarity orresolution has been selected, still or moving images and other contentcaptured from the selected imaging device may be subjected to one ormore analyses. Some such analyses may extract one or more features orattributes from the content, parse or otherwise arrange the featuresinto a defined structure and identify a subset of the defined structurethat refers to the extracted features as functions of time or space.Once the defined structure has been established using audio and/or videocontent captured from one or more imaging devices, the extractedfeatures may be analyzed to determine whether such features correspondwith one or more items, conditions, statuses or events.

According to one such embodiment, a selected imaging device may bepreprogrammed to recognize an item, a condition, a status or an event,according to any given triggering events or metrics, or other relevantthresholds associated with the images, which may be of any relevantcompression or scalable quality, or other content that may be capturedby the selected device. When a selected device recognizes one or morepredefined items, conditions, statuses or events, an indicator such asan electronic signal or an alarm may be provided to a monitoring entityor individual, i.e., on a computer display, or by any other computeroutput device such as a speaker or printer, or in another format, suchas a text message or electronic mail message, and any action may betaken in response to the signal or alarm.

Using the locations, the orientations and the operational capacities ofthe imaging devices, one or more models of a field of view or a coveragezone for each of the imaging devices may be generated, and the object orarea of interest may be back-projected into one or more of such fieldsof view or zones according to an optical transfer function of theimaging device. The optical transfer function may provide for amathematical transformation that converts the coordinates associatedwith objects in free space to coordinates associated with the objects inan image captured by the imaging device based on factors such as theposition of the imaging device (e.g., the x-, y- and z-coordinates ofthe imaging device), the angles (e.g., the roll, pitch and yaw angles)of the axis of orientation of the imaging device, and the coordinates ofthe objects (e.g., the x-, y- and z-coordinates of the imaging device).The optical transfer function may thus take the form of atwo-dimensional array representative of pixel intensity and pixelpositions that translates real data to image data, or vice versa.

For example, a imaging device transformation or projectiontransformation may determine relations between the real-world locationsand/or orientations of objects or areas of interest (i.e., in threedimensions) to the modeled fields of view, in order to determine whichof the imaging devices may cover the object or the area of interest, andwhich of the pixels within images captured by such imaging devicesinclude the object or the area of interest, e.g., by determining adistance of the object or the area of interest to an origin defined bythe imaging device, and dimensions above, below and around the objectwithin the field of view of the imaging devices at the distance from theorigin. The information or variables associated with the imaging devicetransformation or projection transformation may be provided in one ormore matrices, which may be scaled proportionally as required in orderto determine the extent to which the object appears within the field ofview of each imaging device.

Such a back-projection may occur in response to a change in state ormotion of the imaging devices, or of the object or the area of interest,and may be used to identify imaging devices, and pixels of imagescaptured by such imaging devices, in which the object or area ofinterest may be found, as well as to determine the quality or resolutionof the images that may be captured using each imaging device.Additionally, the imaging devices or pixels to be evaluated may beselected in real time or in near-real time with respect to imagingdevices that are operating, or forensically with respect to imagingdevices that were operating at a prior time.

The systems and methods disclosed herein may provide a number ofadvantages over systems and methods of the prior art. For example, suchsystems and methods may result in savings of cost and labor indetermining which of a plurality of imaging devices may be selectedand/or operated in order to evaluate an object or area of interest at agiven location. Additionally, such systems and methods may furtherenable greater efficiency in scheduling or prioritizing the operation ofone or more specific imaging devices, by permitting users to selectivelyoperate imaging devices that may access or capture information regardingthe object or area of interest. Furthermore, the systems and methodsdisclosed herein enable the forensic analysis of images obtained using aplurality of imaging devices by automatically identifying which of theimaging devices may have captured images of an object or area ofinterest, and which could not have captured any such images.

Accordingly, the systems and methods disclosed herein may be utilized innearly any application in which multiple imaging devices may beprovided. Such applications may include the monitoring of traffic flow,the protection of one or more secure facilities, e.g., a fulfillmentcenter, or any other like operations.

Referring to FIG. 2, a block diagram of one system 200 for automaticallyselecting imaging devices for video analytics is shown. The system 200includes a warehouse 210, an online marketplace 250 and an external user260 that are connected to one another across an external network 270,such as the Internet.

The warehouse 210 may be any facility that is adapted to receive, store,process and/or distribute items, such as a fulfillment center, and mayinclude any apparatuses that may be required in order to receiveshipments of items from one or more sources and/or through one or morechannels, including but not limited to docks, lifts, cranes, jacks,belts or other conveying apparatuses for obtaining items and/orshipments of items from carriers such as cars, trucks, trailers, freightcars, container ships or cargo aircraft (e.g., manned aircraft orunmanned aircraft, such as drones), and preparing such items for storageor distribution to customers. The warehouse 210 may also include one ormore storage areas having predefined two-dimensional orthree-dimensional spaces for accommodating items and/or containers ofsuch items, such as aisles, rows, bays, shelves, slots, bins, racks,tiers, bars, hooks, cubbies or other like storage means, or any otherappropriate regions or stations. The warehouse 210 may further includeone or more regions or stations where items that have been retrievedfrom a designated storage area may be evaluated, prepared and packed fordelivery to addresses, locations or destinations specified by customers,also by way of carriers such as cars, trucks, trailers, freight cars,container ships or cargo aircraft (e.g., manned aircraft or unmannedaircraft, such as drones).

As is shown in FIG. 2, the warehouse 210 includes a plurality of imagingdevices 220A, 220B, 220C, 220D and a user 230 that are connected to oneanother across an internal network 240, along with a plurality ofcomputer-related components, including a server 242, a processor 244 anda data store 246. The imaging devices 220A, 220B, 220C, 220D maycomprise any form of optical recording device that may be used tophotograph or otherwise record images of structures, facilities or otherelements within the warehouse 210, as well as the items within thewarehouse 210, or for any other purpose. Such imaging devices 220A,220B, 220C, 220D may capture one or more still or moving images, as wellas any relevant audio signals or other information, within one or moredesignated locations within the warehouse 210, and may be connected toone another by way of the internal network 240, as indicated by lines225A, 225B, 225C, 225D, by the transmission and receipt of digital data.Additionally, the imaging devices 220A, 220B, 220C, 220D may be adaptedor otherwise configured to communicate with one another, or with theuser 230, the server 242, the processor 244 or the data store 246, or toaccess one or more other computer devices by way of the external network270, over the internal network 240. Although the warehouse 210 of FIG. 2includes four imaging devices 220A, 220B, 220C, 220D, any number or typeof imaging devices may be provided in accordance with the presentdisclosure, including but not limited to imaging devices or otheroptical sensors.

The user 230 may be an entity or individual that utilizes one or moreorder processing and/or communication systems using a computing devicesuch as the workstation 232 or any other like machine that may operateor access one or more software applications including one or more userinterfaces 234 (e.g., a browser), or through one or more other computingmachines that may be connected to the internal network 240 or theexternal network 270, as is indicated by line 235, in order to transmitor receive information in the form of digital or analog data, or for anyother purpose. The workstation 232 may also operate or provide access toone or more reporting systems for receiving or displaying information ordata regarding workflow operations, and may provide one or moreinterfaces, such as the user interface 234, for receiving interactions(e.g., text, numeric entries or selections) from one or more operators,users or workers in response to such information or data. Theworkstation 232 may further operate or provide access to one or moreengines for analyzing the information or data regarding the workflowoperations, or the interactions received from the one or more operators,users or workers.

For example, the user 230 may review information identified by theimaging devices 220A, 220B, 220C, 220D on the user interface 234, accessany information or execute any commands using the server 242, theprocessor 244 or the data store 246, or perform any other functions,using the workstation 232, which may be a general purpose device such apersonal digital assistant, a digital media player, a smartphone, atablet computer, a desktop computer or a laptop computer, and mayinclude any form of input and/or output peripherals such as scanners,readers, keyboards, keypads, touchscreens or like devices. Theworkstation 232 may be connected to or otherwise communicate with theimaging devices 220A, 220B, 220C, 220D, the server 242, the processor244 and/or the data store 246, through the internal network 240, asindicated by line 235, by the transmission and receipt of digital data.Additionally, the workstation 232 may be connected to or otherwisecommunicate with the online marketplace 250 or the external user 260through the external network 270, by way of a connection 275 between theinternal network 240 and the external network 270.

The warehouse 210 may also maintain one or more control systems forconducting operations at one or more receiving stations, storage areasor distribution stations. Such control systems may be associated withthe workstation 232 or one or more other computing machines, and mayinclude one or more physical computer devices or servers 242, processors244 or data stores 246, which may be configured to transmit, process orstore any type of information, including but not limited to informationregarding locations and/or orientations of imaging devices, or locationsof objects or areas of interest.

Additionally, such control systems may communicate with the onlinemarketplace 250 or the external user 260, as well as one or more workersor staff members, including but not limited to the user 230, who mayhandle or transport items within the warehouse 210. Such workers mayoperate one or more computing devices for registering the receipt,retrieval, transportation or storage of items within the fulfillmentcenter, such as the workstation 232, or a general purpose device such apersonal digital assistant, a digital media player, a smartphone, atablet computer, a desktop computer or a laptop computer, and mayinclude any form of input and/or output peripherals such as scanners,readers, keyboards, keypads, touchscreens or like devices.

The internal network 240 may be any wired network, wireless network, orcombination thereof, such as a personal area network, local areanetwork, wide area network, cable network, satellite network, cellulartelephone network, or combination thereof that may be associated withcomputer-based operations within the warehouse 210. For example, theinternal network 240 may be a publicly accessible network of linkednetworks, possibly operated by various distinct parties, such as theInternet. In some embodiments, the internal network 240 may be a privateor semi-private network, such as a corporate or university intranet. Theinternal network 240 may include one or more wireless networks, such asa Global System for Mobile Communications (GSM) network, a Code DivisionMultiple Access (CDMA) network, a Long Term Evolution (LTE) network, orsome other type of wireless network. Protocols and components forcommunicating via the Internet or any of the other aforementioned typesof communication networks are well known to those skilled in the art ofcomputer communications and thus, need not be described in more detailherein.

The marketplace 250 may be owned or operated any entity or individualthat sells or otherwise makes items available from one or more sources(e.g., merchants, vendors, sellers, distributors or manufacturers ofsuch items), for download, purchase, rent, lease or borrowing bycustomers. Additionally, the marketplace 250 itself may also be avendor, a seller, a distributor or a manufacturer of the items that areto be made available there.

The marketplace 250 may include or operate one or more physical computerdevices, such as a computer 252 or any other like machine that mayoperate or access one or more software applications including one ormore user interfaces 254. The computer 252 may be connected to orotherwise communicate with the warehouse 210 or the external user 260through the network 270, as indicated by line 255, by the transmissionand receipt of digital data. Additionally, the marketplace 250 maymaintain a marketplace network site that may be implemented using one ormore servers or data stores (not shown). The network site may bemaintained in the form of programmed code, which may be generatedmanually or automatically, and in accordance with any schedule, such asin real time or in near-real time, or in one or more batch processes.Additionally, the marketplace 250 may feature software applicationsand/or hardware components for analyzing data received from merchants,or from customers, including data regarding merchants' productofferings, prices and any relevant accounting information, as well asdata regarding customers' movements, actions, preferences, purchasinghistories or personal information. The marketplace 250 and the computer252, as well as any associated servers, data stores or network sites,may be connected to or otherwise communicate with customers by sendingand receiving digital data over the external network 270, as indicatedby lines 255.

In some embodiments, the marketplace 250 may correspond to a logicalassociation of one or more computing devices, such as an applicationserver for generating recommendations and determining consumptionclasses for users and content as described in greater detail below; anetwork server for creating and transmitting user interfaces; or adatabase server for storing data regarding users, items, etc. In someembodiments, the features and services provided by the marketplace 250may be implemented as network services or web services consumable viathe external network 270. In further embodiments, the marketplace 250 isprovided by one more virtual machines implemented in a hosted computingenvironment. The hosted computing environment may include one or morerapidly provisioned and released computing resources, which computingresources may include computing, networking and/or storage devices. Ahosted computing environment may also be referred to as acloud-computing environment.

The external user 260 may be any entity or individual, other than theuser 230, that utilizes one or more computing devices, such as theworkstation 262 or any other like machine that may operate or access oneor more software applications including one or more user interfaces 264.The workstation 262 may be connected to or otherwise communicate withthe warehouse 210 or the online marketplace 250 through the network 270,as indicated by line 265, by the transmission and receipt of digitaldata. For example, the external user 260 may review informationidentified by any of the imaging devices 220A, 220B, 220C, 220D on theuser interface 264, or perform any other functions using the workstation262, which, like the computer 232, may be a general purpose device sucha personal digital assistant, a digital media player, a smartphone, atablet computer, a desktop computer or a laptop computer, and mayinclude any form of input and/or output peripherals such as scanners,readers, keyboards, keypads, touchscreens or like devices.

The external network 270 may be any wired network, wireless network, orcombination thereof. In addition, the external network 270 may be apersonal area network, local area network, wide area network, cablenetwork, satellite network, cellular telephone network, or combinationthereof. Like the internal network 240, the external network 270 may bea publicly accessible network of linked networks, possibly operated byvarious distinct parties, such as the Internet. In some embodiments, theexternal network 270 may be a private or semi-private network, such as acorporate or university intranet. The external network 270 may includeone or more wireless networks, such as a Global System for MobileCommunications (GSM) network, a Code Division Multiple Access (CDMA)network, a Long Term Evolution (LTE) network, or some other type ofwireless network. Protocols and components for communicating via theInternet or any of the other aforementioned types of communicationnetworks are well known to those skilled in the art of computercommunications and thus, need not be described in more detail herein.

The computers, servers, devices and the like described herein have thenecessary electronics, software, memory, storage, databases, firmware,logic/state machines, microprocessors, communication links, displays orother visual or audio user interfaces, printing devices, and any otherinput/output interfaces to provide any of the functions or servicesdescribed herein and/or achieve the results described herein. Also,those of ordinary skill in the pertinent art will recognize that usersof such computers, servers, devices and the like may operate a keyboard,keypad, mouse, stylus, touch screen, or other device (not shown) ormethod to interact with the computers, servers, devices and the like, orto “select” an item, link, node, hub or any other aspect of the presentdisclosure.

Those of ordinary skill in the pertinent arts will understand thatprocess steps described herein as being performed by a “user” or by a“warehouse” may be automated steps performed by their respectivecomputer systems, or implemented within software modules (or computerprograms) executed by one or more general purpose computers. Moreover,process steps described as being performed by a “user” or by a“warehouse” may be typically performed by a human operator, but could,alternatively, be performed by an automated agent. Moreover, those ofordinary skill in the pertinent arts will further understand thatprocess steps described herein as being performed using a “camera” maybe performed using any form of imaging device, or any type of sensor.

The warehouse 210, the imaging devices 220A, 220B, 220C, 220D, theworkstation 232, the marketplace 250, the computer 252 and/or theexternal user 260 or workstation 262 may use any web-enabled or Internetapplications or features, or any other client-server applications orfeatures including electronic mail (or E-mail), or other messagingtechniques, to connect to the external network 270 or to communicatewith one another, such as through short or multimedia messaging service(SMS or MMS) text messages. For example, the imaging devices 220A, 220B,220C, 220D may be adapted to transmit information or data in the form ofsynchronous or asynchronous messages to the workstation 232, thecomputer 252 or the workstation 262 or another computer device in realtime or in near-real time, or in one or more offline processes, via theinternal network 240 and/or the external network 270. Those of ordinaryskill in the pertinent art would recognize that the user 230, themarketplace 250 and/or the external user 260 may operate any of a numberof computing devices that are capable of communicating over the network,including but not limited to set-top boxes, personal digital assistants,digital media players, web pads, laptop computers, desktop computers,electronic book readers, and the like. The protocols and components forproviding communication between such devices are well known to thoseskilled in the art of computer communications and need not be describedin more detail herein.

The data and/or computer executable instructions, programs, firmware,software and the like (also referred to herein as “computer executable”components) described herein may be stored on a computer-readable mediumthat is within or accessible by computers, such as the workstation 232,the computer 252 or the workstation 262, or any computers or controlsystems utilized by the user 202, the marketplace 250 and/or theexternal user 260 and having sequences of instructions which, whenexecuted by a processor (e.g., a central processing unit, or “CPU”),cause the processor to perform all or a portion of the functions,services and/or methods described herein. Such computer executableinstructions, programs, software and the like may be loaded into thememory of one or more computers using a drive mechanism associated withthe computer readable medium, such as a floppy drive, CD-ROM drive,DVD-ROM drive, network interface, or the like, or via externalconnections.

Some embodiments of the systems and methods of the present disclosuremay also be provided as a computer executable program product includinga non-transitory machine-readable storage medium having stored thereoninstructions (in compressed or uncompressed form) that may be used toprogram a computer (or other electronic device) to perform processes ormethods described herein. The machine-readable storage medium mayinclude, but is not limited to, hard drives, floppy diskettes, opticaldisks, CD-ROMs, DVDs, ROMs, RAMs, erasable programmable ROMs (“EPROM”),electrically erasable programmable ROMs (“EEPROM”), flash memory,magnetic or optical cards, solid-state memory devices, or other types ofmedia/machine-readable medium that may be suitable for storingelectronic instructions. Further, embodiments may also be provided as acomputer executable program product that includes a transitorymachine-readable signal (in compressed or uncompressed form). Examplesof machine-readable signals, whether modulated using a carrier or not,may include, but are not limited to, signals that a computer system ormachine hosting or running a computer program can be configured toaccess, or including signals that may be downloaded through the Internetor other networks.

As is discussed above, one or more imaging devices, or areas of pixelswithin fields of view of the imaging devices, may be identified asincluding an object or area of interest within a coverage zone thereofbased on information regarding locations of the imaging devices and theobject or area of interest, as well as information that may be knownregarding the operational properties (e.g., orientations, attributes orcapacities) of the imaging devices. Once a imaging device, or an area ofpixels within a field of view of the imaging device, has been identifiedas including the object or area of interest therein, one or more alertor alarm conditions may be established for the imaging device or thearea of pixels, such that any change, motion or other predeterminedaction occurring within the field of view of the imaging device or thearea of pixels results in an alert or an alarm. Referring to FIG. 3, aflow chart 300 representing one embodiment of a process forautomatically selecting imaging devices for video analytics inaccordance with embodiments of the present disclosure is shown. At box310, locations, orientations and capacities of a plurality of imagingdevices in a three-dimensional free space are identified. Such imagingdevices may be installed or otherwise provided in an array or otherdefined layout, e.g., in designated locations within a warehouse, afulfillment center or other like facility.

At box 320, the fields of view for each of the plurality of imagingdevices are defined. For example, based on information regarding thelocations, orientations and capacities of the plurality of imagingdevices identified at box 310, such as the coordinates x_(C), y_(C),z_(C), the angle of view γ_(C) and the axis of orientation AXIS_(C)defined by the roll angle ω_(C), the pitch angle φ_(C) or the yaw angleκ_(C) for the imaging device 120C of FIG. 1C, as well as thecorresponding coordinates and angles for the imaging devices 120A, 120B,120D of FIGS. 1A and 1B, one or more geometric or mathematical models(e.g., virtual conical or pyramidal sections) of the fields of view ofthe plurality of imaging devices may be determined with respect to thefree space. One model of a field of view of a imaging device may includea virtual conical or pyramidal section having an origin at a lens of theimaging device and an angle defined by a dimension of an image sensorand a focal length between the lens and the image sensor, as well as anaxis of orientation defined by a roll angle, a pitch angle and a yawangle of the lens. Such fields of view may also be determined asfunctions of the respective positions, focal lengths or angles of theimaging devices, and may be fixed or variable depending on thecapacities of the imaging devices. For example, where an imaging deviceincludes an optical zoom or digital zoom function and a mounting thatmay be panned or tilted, the field of view may be expressed in one ormore variables or functions of time.

At box 330, a location of the object for which evaluation is desired maybe determined. For example, referring again to FIGS. 1A and 1B, thecoordinates x₁, y₁, z₁ or other information associated with the locationof the object 102 may be identified. At box 340, the fields of view ofthe imaging devices in which the object may be located are identified.For example, using one or more models that may be generated based on thelocations, orientations and capacities of the imaging devices identifiedat box 310, the one or more imaging devices that include the objectwithin a field or view, or may be adjusted to include the object withina field of view, may be identified.

At box 350, a projection transformation for the object within the fieldsof view may be determined, e.g., according to an optical transferfunction. For example, the dimensions of the object within each of thefields of view of imaging devices in which the object may be found maybe determined using the locations, orientations and capacities of therespective imaging devices identified at box 310, as well as thelocation of the object identified at box 330, through one or moregeometric techniques. As is discussed above, an optical transferfunction may mathematically transform the coordinates associated withthe object in free space to coordinates associated with the object in animage captured by the imaging device based on factors such as theposition of the imaging device, the angles of the axis of orientation ofthe imaging device, and the coordinates of the objects. At box 360, theimaging devices having the most effective views of the object based onthe fields of view and the projection transformation are identified.Such views may be defined by the sizes, clarity or resolution of theimages of the object, or according to any desired standard.

At box 370, a pixel area of the fields of view of the imaging devicesmay be outlined for a relevant alert, and the process ends. The pixelarea may encompass all or a portion of the fields of view, and therelevant alert may be defined based on any detection or determinationthat an item is present, or that a condition, a status or an event hasoccurred, according to any given triggering events or metrics, or otherrelevant thresholds. Once the parameters of the relevant alert have beendefined with respect to images captured in or by one or more imagingdevices or fields of view, the systems and methods disclosed herein mayengage in persistent or scheduled monitoring of the object, and thedetection or determination of the item, the condition, the status or theevent may trigger or otherwise cause any relevant action to occur inresponse to the detection or determination, such as the sounding of analarm, the transmission of one or more messages, or any other response.

Accordingly, the systems and methods of the present disclosure mayenable the selection of one or more appropriate imaging devices formonitoring an object or area of interest, and any relevant informationassociated with the object or the area of interest may be identifiedthrough a content-based analysis of still or moving images captured ofthe object or the area of interest. Referring to FIGS. 4A and 4B, viewsof one system 400 for automatically selecting imaging devices for videoanalytics in accordance with embodiments of the present disclosure areshown. The system 400 includes a warehouse 410 or fulfillment centerhaving a gate 402 and security fence 404.

Additionally, the system 400 further includes a plurality of imagingdevices 420A, 420B, 420C, 420D, 420E mounted to the warehouse 410, aswell as imaging devices 420F, 420G mounted outside the gate 402 andsecurity fence 404. As is shown in FIGS. 4A and 4B, each of the imagingdevices 420A, 420B, 420C, 420D, 420E, 420F, 420G provides a field ofview FOV_(A), FOV_(B), FOV_(C), FOV_(D), FOV_(E), FOV_(F), FOV_(G)oriented toward the gate 402 and/or the security fence 404.

As is discussed above, the systems and methods of the present disclosureare directed to selecting one or more imaging devices, such as one ormore of imaging devices 420A, 420B, 420C, 420D, 420E, 420F, 420G ofFIGS. 4A and 4B, for the purpose of monitoring an object or area ofinterest, such as the gate 402 or the security fence 404 of FIGS. 4A and4B, based on the location of the object or area of interest, and thelocations and operational attributes of the imaging devices. One or moregeometric or mathematical models of the fields of view provided by theimaging devices (e.g., conical or pyramidal sections representative ofsuch fields of view) may be generated and used to determine whether orwhich imaging devices may have a view of the object or area of interest.Once such imaging devices may be identified, a set of conditions orthresholds associated with the object or area of interest may bedefined, and the systems and methods disclosed herein may be configuredto take one or more actions in response to events that satisfy one ormore of the conditions, or exceed one or more of the thresholds.

For example, where a selected one of the imaging devices 420A, 420B,420C, 420D, 420E, 420F, 420G of FIGS. 4A and 4B detects an operation ofthe gate 402 or any form of breach of the security fence 404 within oneor more predefined areas of a field of view, an alert or alarm signalmay be generated, and one or more actions may be taken in response tothe signal. Additionally, if multiple imaging devices may include theobject or area of interest within their respective fields of view, aimaging device having a preferred or superior view of the object or areaof interest may be selected, or multiple imaging devices may be used todetermine whether one or more of the conditions has been satisfied, orone or more of the thresholds has been exceeded.

Referring to FIG. 5, a flow chart 500 representing one embodiment of aprocess for automatically selecting imaging devices for video analyticsin accordance with embodiments of the present disclosure is shown. Atbox 510, information regarding one or more alarm-triggering events isprogrammed into a system having a plurality of imaging devices. Suchinformation may relate to an item, a condition, a status or an event,such as an operation of the gate 402 or a breach of the security fence404 of FIGS. 4A and 4B, a movement of the object 102 of FIGS. 1A and 1B,or any other general or specific occurrence.

At box 520, the locations, orientations and/or focal lengths of all ofthe imaging devices in the system are determined. Such locations andorientations may be expressed according to any defined coordinatestandard, e.g., a Cartesian or polar coordinate system, and thelocations, orientations or focal lengths may be fixed or adjustabledepending on the corresponding capacities of the respective imagingdevices. At box 530, the coordinates of the locations and orientations,and the focal lengths, may be used to define one or more coverage zonesfor each of the imaging devices. Where the imaging devices arestationary and have fixed orientations and focal lengths, the coveragezones defined according to such locations, orientations or focal lengthsare similarly fixed. Where the imaging devices have one or moreadjustable features, including structures or mounts which permit theimaging devices to change their locations or orientations, or to adjusttheir focal lengths, however, such coverage zones may be expressed asfunctions of space and/or time.

At box 540, the locations of an object or an area of interest may beidentified, and expressed in coordinates. Such locations may also befixed or adjustable, depending on the object or the area of interest,and may be expressed in the same coordinate standard as the locations ofthe imaging devices that were determined at box 520. At box 550, one ormore imaging devices having the object or the area of interest withinthe coverage zone may be identified, and at box 560, the extent ofcoverage of the object or the area of interest by each of the imagingdevices may be determined. For example, the locations of the objects orareas of interest identified at box 540 may be back-projected through aimaging device transformation according to an optical transfer function,in order to determine which of the imaging devices include the object ina field of view, and which of the pixels of the images captured by suchimaging devices include the object. A coverage zone for an imagingdevice may be defined by a field of view of the imaging device, or asubset of the field of view, which may be further defined by a number orlocation of pixels within the field of view.

At box 570, one or more appropriate imaging devices for monitoring theobject or the area of interest are selected. For example, once thespecific locations of the objects or areas of interest within the fieldsof view are identified, such as with regard to the number or locationsof the pixels within the fields of view, the imaging devices having thebest or most appropriate views of the object or the area of interest maybe chosen for monitoring purposes. At box 580, the system determineswhether one or more of the alarm-triggering events are observed. Forexample, where the system is programmed to recognize an operation of thegate 402 or a breach of the security fence 404 of FIGS. 4A and 4B, or amovement of the object 102 of FIGS. 1A and 1B within fields of view ofone or more of the plurality of imaging devices, the system mayrecognize, through a content-based analysis of the still and/or movingimages captured by the selected imaging devices, whether one or moresuch a breach or movement has occurred.

If an alarm-triggering event defined by the information programmed intothe system at box 510 has occurred, then the process advances to box585, where an alarm relating to the alarm-triggering event is issued.Such an alarm may comprise an electronic signal (e.g., an audio or videosignal), a transmission of one or more electronic messages, or any otherappropriate action in response to the alarm. In some embodiments, oneset of actions in response to the alarm may be to focus or reorient oneor more additional imaging devices, such as one or more of the imagingdevices 420A, 420B, 420C, 420D, 420E, 420F, 420G of FIG. 4A or 4B, orthe imaging devices 120A, 120B, 120C, 120D of FIG. 1A or 1B, to gainadditional information regarding the alarm-triggering event or theassociated object or area of interest.

If no such alarm-triggering event is observed, then the process advancesto box 590, where the system continues to monitor the object or the areaof interest identified at box 540, and to box 595, where the systemprompts a user for additional objects or areas of interest that are tobe monitored. If no additional objects or areas of interest are to bemonitored, then the process ends. If any such objects or areas ofinterest are to be monitored, however, then the process returns to box540, where the locations of such objects or areas of interest areidentified in coordinates, such as the same coordinate standard as thelocations of the imaging devices that were determined at box 520, andthe process ends.

Accordingly, by selecting an imaging device, or a portion of a field ofview of the imaging device, having a view of an object or an area ofinterest, the systems and methods of the present disclosure may beprogrammed to recognize an item, a condition, a status or an event, andto generate an alert or alarm, such as an audio or visual alarm, anelectronic message or other identifier, in response to the recognitionof the item, the condition, the status or the event.

As is also discussed above, the systems and methods of the presentdisclosure may be configured to identify which of a plurality of imagingdevices, or portions of fields of view of such imaging devices, includesan object or an area of interest in hindsight, based on the location ofthe object or the area of interest, and the locations and operationalproperties of the imaging devices. In this regard, where an event ofinterest has occurred in a vicinity of a number of operating imagingdevices, the imaging devices which may have captured images of the eventof interest may be forensically identified by generating models of thefields of view of each of the imaging devices and comparing such modelsto the location at which the event of interest occurred.

Referring to FIG. 6, a flow chart 600 representing one embodiment of aprocess for automatically selecting imaging devices for video analyticsin accordance with embodiments of the present disclosure is shown. Atbox 610, a notification regarding the occurrence of an event of interestis received. The occurrence may be identified manually or automatically,such as in response to a signal generated by a motion sensor, a securityalarm, or the like.

At box 620, a location at which the event of interest occurred isidentified. The location may be identified by any means or method, andmay be referenced in terms of coordinates or other identifyinginformation or data according to any standard. At box 630, the operatinghistories of a plurality of imaging devices at a time of the event ofinterest are determined. For example, the number of a plurality ofimaging devices in a vicinity of the location of the event of interest,and the times at which each of the plurality of imaging devices wasoperating, may be identified. At box 640, the locations, orientationsand capacities of the imaging devices that were operating at the time ofthe event of interest are identified. Such locations and orientationsmay be expressed in terms of coordinates and/or angles or axes oforientation (e.g., x-, y- and z-coordinates of imaging devices, as wellas roll, pitch and yaw angles of axes of orientation of the imagingdevices), and the operational features available to such imaging devices(e.g., panning or tilting mounts, adjustable focal lengths) may also beidentified.

At box 650, the imaging devices that were operating at the time of theevent of interest and included the location of the event of interest maybe forensically determined based on the operating histories of theimaging devices, and the locations of the imaging devices and the eventof interest. For example, one or more static or variable models of thefields of view of a plurality of imaging devices as of the time of theevent of interest may be generated, and the models of the fields of viewand the locations at which the event of interest occurred may beback-projected through a imaging device transformation according to anoptical transfer function. Whether any of the fields of view includedthe event of interest may be determined based on a comparison of thelocation of the identified at box 620 to the models of the fields ofview, according to the optical transfer function.

At box 660, the event of interest may be reconstructed using informationthat was captured by one or more of the imaging devices at the time ofthe event of interest, and the process ends. For example, atwo-dimensional or three-dimensional model of the location of the eventof interest, as of the time of the event of interest, may be generatedbased at least in part on one or more photogrammetric analyses of imagescaptured by one or more imaging devices, which may be configured to notonly identify outlines of objects but also distinguish specific objectswithin such images.

Accordingly, the systems and methods disclosed herein may be used notonly to identify one or more imaging devices, or portions of fields ofview (e.g., sets of pixels) of such imaging devices, that may include anobject or area of interest therein, and to monitor for informationrelating to items, conditions, statuses or events associated with suchobjects or interests in the future, but also to identify one or moreimaging devices, or portions of fields of view of such imaging devices,which may have captured information regarding an event of interest thathas already occurred. Such imaging devices or portions of fields of viewmay be identified based on any information that may be known regardingeither the event of interest or the relevant imaging devices, includingthe locations at which the event of interest occurred or the relevantimaging devices are positioned, as well as the operational properties(e.g., orientations, attributes or capacities) of the relevant imagingdevices.

As is discussed above, the systems and methods disclosed herein may beutilized in any application where a plurality of imaging devices areprovided for the purpose of monitoring objects or areas of interest forinformation relating to items, conditions, statuses or events. Referringto FIG. 7, a system 700 for automatically selecting imaging devices forvideo analytics in accordance with embodiments of the present disclosureare shown. The system 700 includes a plurality of individuals 702A,702B, 702C, 702D, a plurality of automobiles 704A, 704B, 704C, 704D anda plurality of facilities 706A, 706B, 706C, 706D, as well as a pluralityof imaging devices 720A, 720B, 720C, 720D.

In some embodiments of the present disclosure, the systems and methodsmay be provided to monitor traffic operations, including the movementsof the vehicles 704A, 704C through the intersection during one trafficflow condition, or the movements or operations of the vehicles 704B,704D during another traffic flow condition. Thus, one or more of theimaging devices 720A, 720B, 720C, 720D may be selected for monitoringsuch flow conditions, based on the locations and respective operationalproperties of the respective imaging devices 720A, 720B, 720C, 720D(e.g., the various fields of view, focal lengths and/or orientations ofthe imaging devices, which may be fixed or variable for each of theimaging devices) and also the locations of the various areas ofinterest, such as a crosswalk entered by the individual 702C, corners atwhich the individuals 702A, 702B, 702D are located, as well as theintersection through which the vehicles 704A, 704C are traveling, and atwhich the vehicles 704B, 704D are stopped, or the buildings 706A, 706B,706C, 706D. In this regard, one or more of the imaging devices 720A,720B, 720C, 720D having a most appropriate or advantageous view of therelevant crosswalks, corners, intersection or buildings may be selected.The selected imaging devices may be programmed or otherwise configuredto recognize predetermined activity associated with the objects or areasof interest, which may be defined according to one or more triggeringevents or metrics.

Additionally, where an event of interest (e.g., an automobile collision,a hit-and-run accident or a fire engulfing one or more of the buildings)has occurred, the systems and methods of the present disclosure mayfurther determine whether any of the imaging devices 720A, 720B, 720C,720D captured information regarding the event of interest, and which ofthe imaging devices 720A, 720B, 720C, 720D may have provided thehighest-quality still or moving images of the event of interest. Suchdeterminations may be based on the locations and respective operationalproperties of the respective imaging devices 720A, 720B, 720C, 720D(e.g., the various fields of view, focal lengths and/or orientations ofthe imaging devices, which may be fixed or variable for each of theimaging devices) and also the location of the event of interest.

Although the disclosure has been described herein using exemplarytechniques, components, and/or processes for implementing the presentdisclosure, it should be understood by those skilled in the art thatother techniques, components, and/or processes or other combinations andsequences of the techniques, components, and/or processes describedherein may be used or performed that achieve the same function(s) and/orresult(s) described herein and which are included within the scope ofthe present disclosure. Additionally, although many of the embodimentsdescribed herein or shown in the accompanying figures refer to the useof imaging devices in fixed positions and/or orientations, the systemsand methods disclosed herein are not so limited, and may be employedwith any form of imaging device, including those imaging devices havingadjustable positions, fields of view or orientations, including but notlimited to PTZ or ePTZ imaging devices, as well as film based imagingdevices. For example, the coverage zones defined in box 530 of FIG. 5may be expressed in terms of a current location, orientation or focallength of a given imaging device, or an extent of the possiblelocations, orientations or focal lengths of the given imaging device asfunctions of time or space. Alternatively, with regard to the operatinghistories, the locations, the orientations or the capacities of theimaging devices identified at box 640 of FIG. 6, such operatinghistories, locations, orientations or capacities may be defined withregard to points in time preceding the time at which the event ofinterest occurred.

It should be understood that, unless otherwise explicitly or implicitlyindicated herein, any of the features, characteristics, alternatives ormodifications described regarding a particular embodiment herein mayalso be applied, used, or incorporated with any other embodimentdescribed herein, and that the drawings and detailed description of thepresent disclosure are intended to cover all modifications, equivalentsand alternatives to the various embodiments as defined by the appendedclaims. Moreover, with respect to the one or more methods or processesof the present disclosure described herein, including but not limited tothe flow charts shown in FIGS. 3, 5 and 6, the order in which the boxesor steps of the methods or processes are listed is not intended to beconstrued as a limitation on the claimed inventions, and any number ofthe boxes or steps can be combined in any order and/or in parallel toimplement the methods or processes described herein. Also, the drawingsherein are not drawn to scale.

Conditional language, such as, among others, “can,” “could,” “might,” or“may,” unless specifically stated otherwise, or otherwise understoodwithin the context as used, is generally intended to convey in apermissive manner that certain embodiments could include, or have thepotential to include, but do not mandate or require, certain features,elements and/or boxes or steps. In a similar manner, terms such as“include,” “including” and “includes are generally intended to mean“including, but not limited to.” Thus, such conditional language is notgenerally intended to imply that features, elements and/or boxes orsteps are in any way required for one or more embodiments or that one ormore embodiments necessarily include logic for deciding, with or withoutuser input or prompting, whether these features, elements and/or boxesor steps are included or are to be performed in any particularembodiment.

Although the invention has been described and illustrated with respectto exemplary embodiments thereof, the foregoing and various otheradditions and omissions may be made therein and thereto withoutdeparting from the spirit and scope of the present disclosure.

What is claimed is:
 1. A method comprising: capturing a plurality ofvideo files from a scene by a plurality of digital cameras over a periodof time, wherein each of the digital cameras defines a field of viewincluding at least a portion of the scene, and wherein the period oftime includes a first time; storing at least some of the video files inat least one data store at a second time, wherein the second timefollows the period of time; after the second time, determining that anevent occurred at a location within the scene at approximately the firsttime; determining, for each of the digital cameras, a coverage zonebased at least in part on each of: a position of the digital camera; anorientation of the digital camera; and a focal length of the digitalcamera; identifying a first one of the coverage zones including thelocation within the scene; identifying a first one of the digitalcameras corresponding to the first one of the coverage zones; andretrieving a first one of the video files captured by the first one ofthe digital cameras from the at least one data store.
 2. The method ofclaim 1, further comprising: generating a model of the field of view ofthe first one of the digital cameras at the first time based at least inpart on the first one of the video files; generating at least oneback-projection of the model into at least a second one of the videofiles captured by at least a second one of the digital cameras accordingto an optical transfer function; and reconstructing the event based atleast in part on the model and the at least one back-projection.
 3. Themethod of claim 1, wherein the location within the scene includes atleast a portion of a secure facility, and wherein determining that theevent has occurred comprises: determining that access to the securefacility was obtained via at least one entryway at approximately thefirst time, and wherein identifying the one of the coverage zonesincluding the location within the scene comprises: determining that theone of the coverage zones includes at least a portion of the at leastone entryway.
 4. The method of claim 1, wherein determining the coveragezone for each of the digital cameras further comprises: processing atleast one of the video files to recognize at least one of an outline, amovement or a figure associated with an object or an area of interestwithin at least one frame; determining a number of pixels or locationsof the pixels covering the outline, the movement or the figureassociated with the object or the area of interest within at least oneframe of each of the video files; and selecting the first one of thevideo files based at least in part on the number of pixels or thelocation of the pixels within the at least one frame of each of thevideo files.
 5. The method of claim 1, wherein determining the number ofpixels or the locations of the pixels comprises: determining coordinatesof the object or the area of interest in three-dimensional space basedat least in part on the at least one of the outline, the movement or thefigure within the at least one frame; and converting the coordinates ofthe object or the area of interest to coordinates within the at leastone frame of each of the video files according to an optical transferfunction.
 6. A method comprising: after a first time, determining thatan event occurred at a location within a field of view of at least oneof a plurality of cameras, wherein the event is determined to haveoccurred at the first time; identifying a plurality of video filescaptured by the plurality of cameras, wherein each of the video filesincludes at least one image frame captured at the first time, andwherein each of the video files is stored in at least one data store;determining information regarding positions of each of the plurality ofcameras at the first time; determining information regarding focallengths of each of the plurality of cameras at the first time;determining information regarding angular orientations of each of theplurality of cameras at the first time; and selecting one of the videofiles based at least in part on the information regarding the positions,the information regarding the focal lengths and the informationregarding the angular orientations of one of the plurality of cameras atthe first time.
 7. The method of claim 6, wherein determining that theevent occurred comprises: determining that an alarm was issued at thelocation at the first time, wherein the alarm includes at least one of:an audible signal; a video signal; or a transmission of an electronicmessage.
 8. The method of claim 6, wherein determining that the eventoccurred comprises at least one of: determining that a portal was openedor closed at the location; determine that a security barrier surroundingthe location was breached; or determining that an object moved at thelocation.
 9. The method of claim 6, wherein determining that the objectmoved at the location comprises: determining that an object was presentwithin a first video frame captured by one of the plurality of camerasprior to the first time; and determining that the object was not presentwithin a second video frame captured by one of the plurality of camerasfollowing the first time.
 10. The method of claim 6, wherein selectingthe one of the video files comprises: defining, for each of theplurality of cameras, a coverage zone for the field of view of thecamera at the first time, wherein each of the coverage zones is definedwith respect to free space at the location, and wherein each of thecoverage zones comprises a substantially pyramidal section defined basedat least in part on the information regarding the positions, theinformation regarding the focal lengths and the information regardingthe angular orientations of each of the plurality of cameras;identifying one of the coverage zones including the location at thefirst time; and determining the one of the plurality of camerascorresponding to the one of the coverage zones, wherein the selected oneof the video files was captured by the one of the plurality of camerascorresponding to the one of the coverage zones.
 11. The method of claim10, wherein each of the coverage zones comprises a subset of pixels ofthe field of view of the one of the plurality of cameras.
 12. The methodof claim 10, wherein selecting the one of the video files furthercomprises: determining locations of pixels covering each of the coveragezones; and initiating video analytics of the video files based at leastin part on the locations of the pixels by the at least one computerprocessor.
 13. The method of claim 10, wherein at least one of theplurality of cameras has at least one of an adjustable focal length, anadjustable location, an adjustable roll angle of rotation, an adjustablepitch angle of rotation or an adjustable yaw angle of rotation, andwherein each of the coverage zones is defined as a function of time. 14.The method of claim 6, wherein selecting one of the video filescomprises: determining a position of an object associated with the eventin three-dimensional space at the first time; mathematicallytransforming the position of the object associated with the event inthree-dimensional space into each of the video files; and identifying,in each of the video files, a subset of pixels corresponding to themathematically transformed position of the object at the first time,wherein the one of the video files is selected based at least in part onthe subsets of pixels.
 15. The method of claim 14, wherein identifyingthe subset of pixels corresponding to the mathematically transformedposition of the object at the first time comprises at least one of:determining a number of pixels covering at least a portion of the objectwithin each of the video files; or determining locations of the pixelscovering at least the portion of the object within each of the videofiles, wherein the one of the video files is selected based at least inpart on the number of the pixels or the locations of the pixels.
 16. Themethod of claim 15, wherein the number of the pixels or the locations ofthe pixels are determined according to an optical transfer function. 17.The method of claim 6, wherein selecting the one of the video filescomprises: identifying, in a first one of the plurality of video files,pixels corresponding to an object associated with the event at thelocation; defining, in the first one of the plurality of video files, anarea of interest including at least the pixels corresponding to theobject; and back-projecting the area of interest into each of theplurality of video files other than the first one of the plurality ofvideo files, wherein the one of the video files is selected based atleast in part on the area of interest or the back-projected areas ofinterest.
 18. The method of claim 6, wherein the information regardingthe angular orientations of the plurality of imaging devices comprisesan angle of view of a lens of the imaging device and an axis oforientation of the imaging device defined by at least one of a rollangle, a pitch angle or a yaw angle.
 19. A monitoring system comprising:a plurality of imaging devices, wherein each of the imaging devices isconfigured to capture media files at a location; and a computing devicein communication with each of the plurality of imaging devices, whereinthe computing device comprises at least one data store and at least onecomputer processor, and wherein the at least one computer processor isconfigured to at least: cause each of the plurality of imaging devicesto capture media files at the location over a period of time; cause eachof the plurality of imaging devices to store the media files in the atleast one data store; determine that an event of interest has occurredat a first time, wherein the first time is within the period of time;identify a position of the event of interest; identify operationalcharacteristics of each of the plurality of imaging devices at the firsttime; identify a field of view for each of the plurality of imagingdevices at the first time; determine whether the field of view of atleast one of the plurality of imaging devices included the position ofthe event of interest at the first time based at least in part on theoperational characteristics of each of the plurality of imaging devicesat the first time; and in response to determining that a field of viewof a first one of the plurality of imaging devices included the positionof the event of interest at the first time, identifying a media filecaptured by the first one of the plurality of imaging devices, whereinthe media file includes at least one frame captured at the first time;and retrieving the media file from the at least one data store.
 20. Themonitoring system of claim 1, wherein the operational characteristics ofat least one of the plurality of imaging devices comprise: a position ofthe at least one imaging device; a roll angle of the at least oneimaging device; a pitch angle of the at least one imaging device; a yawangle of the at least one imaging device; or a focal length of the atleast one imaging device, and wherein the at least one computerprocessor is configured to at least: determine, for each of theplurality of imaging devices, a geometric model of the field of view ofthe imaging device according to a coordinate system, wherein thegeometric model is based at least in part on the operationalcharacteristics of the imaging device; identify a set of coordinatesassociated with the position of the event of interest according to thecoordinate system; and determine, for each of the plurality of imagingdevices, whether the set of coordinates associated with the position ofthe event of interest is within the geometric model of the field of viewof the imaging device.